Mechanical arm control method and device and self-moving cleaning equipment

Abstract

The invention provides a mechanical arm control method and device and self-moving cleaning equipment. The method comprises the steps that working parameters of a mechanical arm of the self-moving cleaning equipment are obtained; and based on the working parameters, the working state of the mechanical arm is determined. According to the technical scheme, the overweight operation of the mechanical arm can be interrupted in time, the situation that the mechanical arm overloads and bears objects for a long time is avoided, the working flexibility and safety of the mechanical arm are improved, the overall performance of the self-moving cleaning equipment can be improved, and the user experience is improved.

Description

[Technical field]

[0001] The present application relates to the field of electrical technology, and in particular to a robot arm control method and device and a self-moving cleaning device. [Background technology]

[0002] With the development of smart electrical appliance technology, self-moving cleaning equipment has become an important cleaning tool that can be used for cleaning homes and public places. In related technologies, in order to further increase the cleaning ability of self-moving cleaning equipment, a mechanical arm is set on the self-moving cleaning equipment, which can be used for tasks such as crossing obstacles, sorting items, sorting garbage, and handling large volumes of garbage.

[0003] However, in actual cleaning work scenarios, the objects that the robotic arm needs to acquire are diverse and their weights vary. Once the weight of the object exceeds the upper limit of the robotic arm's object acquisition capability, forcibly grasping the object will cause the structure and parts of the robotic arm to bear forces beyond its own safe bearing range, placing the robotic arm in an unsafe working state, affecting the life of the robotic arm and may even directly cause damage to the robotic arm.

[0004] Therefore, how to effectively identify whether the robotic arm is in an unsafe working state so as to take timely countermeasures against the unsafe working state has become a technical problem that needs to be solved urgently. [Summary of the invention]

[0005] The embodiments of the present application provide a robot arm control method and device and a self-moving cleaning device, which aim to solve the technical problem in the related art that it is difficult to effectively identify the abnormal working state of the robot arm, which causes the robot arm to be easily damaged.

[0006] In a first aspect, an embodiment of the present application provides a method for controlling a robotic arm, comprising:

[0007] Obtaining the working parameters of the robot arm of the self-mobile cleaning device;

[0008] Based on the working parameters, the working state of the robotic arm is determined.

[0009] In one embodiment of the present application, optionally, the working parameters of the mechanical arm of the mobile cleaning device obtained include:

[0010] The working parameters of the mechanical arm of the self-moving cleaning device when performing an object acquisition action are obtained, wherein the object acquisition action includes at least one of clamping, grabbing, and lifting.

[0011] In one embodiment of the present application, optionally, the working parameters of the mechanical arm of the mobile cleaning device obtained include:

[0012] The working parameters of the robot arm of the self-moving cleaning device when not performing an object acquisition action are obtained.

[0013] In one embodiment of the present application, optionally, the working parameters are acquired in real time.

[0014] In one embodiment of the present application, optionally, the working parameters of the mechanical arm of the mobile cleaning device obtained include:

[0015] Obtain at least one of the quadrature-axis current, arm length, preset calibration coefficient, moment of inertia, angular acceleration and friction torque of at least one joint motor of the robotic arm, wherein the preset calibration coefficient is used to reflect the proportional relationship between the quadrature-axis current and the output torque in the at least one joint motor.

[0016] In one embodiment of the present application, optionally, obtaining the quadrature-axis current of at least one joint motor of the robotic arm includes:

[0017] The three-phase current of the at least one joint motor is collected, and the three-phase current is subjected to a Clark transformation to obtain the quadrature-axis current corresponding to the at least one joint motor.

[0018] In one embodiment of the present application, optionally, obtaining the arm length of at least one joint motor of the robotic arm includes:

[0019] For each joint motor of at least one joint motor of the robotic arm, the force arm length of the joint motor is determined as:

[0020]

[0021] Wherein, r represents the current arm length of the joint motor, n is the number of arm segments from the last arm segment of the robot arm to the current arm segment corresponding to the current joint motor, i represents the arm segment number, i∈[1,n], wherein the arm segment number of the last arm segment is 1, the arm segment number of the current arm segment is n, l i represents the arm length from the last arm section to the i-th arm section in the current arm section, θ i represents the angle between the i-th arm segment and the plane where the self-moving cleaning device is located.

[0022] In one embodiment of the present application, optionally, the method further includes:

[0023] If the current arm segment is the first arm segment of the robot arm closest to the self-moving cleaning device, determine θ i is the angle between the first arm section and the plane where the self-propelled cleaning device is located;

[0024] If the current arm segment is not the first arm segment, θ i =θ i+1 -μ i , where μ i represents the offset angle of the i-th arm segment relative to the i+1-th arm segment.

[0025] In one embodiment of the present application, optionally, determining the working state of the robot arm based on the working parameter includes:

[0026] Based on the working parameters, the weight of the object when the robot arm performs an object acquisition action is determined.

[0027] In one embodiment of the present application, optionally, determining the working state of the robot arm based on the working parameter includes:

[0028] Based on the working parameters, determining the object acquisition weight of the at least one joint motor;

[0029] Based on the object acquired weight of the at least one joint motor, the working state of the at least one joint motor of the robot arm is determined.

[0030] In one embodiment of the present application, optionally, determining the object acquisition weight of the at least one joint motor based on the working parameter includes:

[0031] For each joint motor of the at least one joint motor, a ratio of a product of the quadrature-axis current of the joint motor and the preset calibration coefficient to the lever arm length is determined as an object weight of the joint motor.

[0032] In one embodiment of the present application, optionally, determining the object acquisition weight of the at least one joint motor based on the working parameter includes:

[0033] Based on the quadrature axis current, arm length, preset calibration coefficient, moment of inertia, angular acceleration and friction torque of at least one joint motor of the robot arm, the object acquisition weight of the at least one joint motor is determined, wherein:

[0034]

[0035] W represents the weight of the object obtained by a single joint motor, I q is the quadrature axis current of a single joint motor, r is the arm length of the arm segment directly driven by the single joint motor, K is the preset calibration coefficient of the single joint motor, α is the angular acceleration of the arm segment directly driven by the single joint motor, j is the moment of inertia of the joint where the single joint motor is located, F fIt is the friction torque in the movement of the arm section directly driven by a single joint motor.

[0036] In one embodiment of the present application, optionally, the obtaining weight of the object based on the at least one joint motor and determining the working state of the at least one joint motor of the robotic arm includes:

[0037] If the object acquired weight of any joint motor of the at least one joint motor is greater than the safety weight threshold, it is determined that the robot arm is in an abnormal working state; otherwise, it is determined that the robot arm is in a normal working state; or

[0038] If the object acquisition weight of any joint motor of the at least one joint motor in the object acquisition weight detection for a continuous specified number of times is greater than the safety weight threshold, it is determined that the robotic arm is in an abnormal working state; otherwise, it is determined that the robotic arm is in a normal working state.

[0039] In one embodiment of the present application, optionally, if it is determined that the robot arm is in an abnormal working state, the method further includes:

[0040] generating a stop object acquisition instruction, and based on the stop object acquisition instruction, controlling the robot arm to cancel the object acquisition action; and

[0041] Generate overweight alarm information.

[0042] In one embodiment of the present application, optionally, before obtaining the working parameters of the mechanical arm of the self-mobile cleaning device, the method further includes:

[0043] Determine the target position of the object to be acquired required by the object acquisition action;

[0044] The current posture of the robot arm is set as the grasping posture for the target position.

[0045] In one embodiment of the present application, optionally, before determining the target position of the object to be acquired required for the object acquisition action, the method further includes:

[0046] The object to be acquired is identified by an object identification device, wherein the object identification device includes at least one of a visual sensor, a laser sensor, an ultrasonic sensor, and an infrared sensor.

[0047] In one embodiment of the present application, optionally, setting the current posture of the robot arm as a grasping posture for the target position includes:

[0048] Based on the target position, the posture configuration information of the robot arm when it is in the grasping posture is determined, wherein:

[0049] The posture configuration information includes:

[0050] The angle between the first arm segment of the mechanical arm closest to the self-moving cleaning device and the plane where the self-moving cleaning device is located;

[0051] An offset angle of each arm segment other than the first arm segment in the robotic arm relative to the preceding arm segment in the direction adjacent to the first arm segment; and

[0052] The arm length of each arm section in the robotic arm.

[0053] In one embodiment of the present application, optionally, before obtaining the working parameters of the mechanical arm of the self-mobile cleaning device, the method further includes:

[0054] In response to a start-up instruction for the robotic arm, it is detected whether each joint motor of the robotic arm is in an effective working state, wherein if each joint motor of the robotic arm is in an effective working state, it is allowed to enter the step of obtaining the working parameters of the robotic arm from the mobile cleaning device.

[0055] In one embodiment of the present application, optionally, after setting the current posture of the robot arm as the grasping posture for the target position, the method further includes:

[0056] The robotic arm is adjusted from the grasping posture to the weighing posture.

[0057] In one embodiment of the present application, optionally, the working parameters of the mechanical arm of the mobile cleaning device obtained include:

[0058] During the adjustment process of adjusting the mechanical arm from the grasping posture to the weighing posture, monitoring the working parameters of the mechanical arm in real time to determine the working state of the mechanical arm based on the working parameters;

[0059] as well as

[0060] If the working state of the robot arm is an abnormal working state, the adjustment process is interrupted and an overweight protection strategy is executed;

[0061] If the working state of the robot arm is a normal working state, continue the adjustment process.

[0062] In one embodiment of the present application, optionally, determining the working state of the robotic arm based on the working parameter further includes:

[0063] If the object acquired weight of any joint motor of the at least one joint motor is greater than the corresponding safety weight threshold, it is determined that the robotic arm is in the abnormal working state; otherwise, it is determined that the robotic arm is in a normal working state; or

[0064] If the object acquisition weight of any joint motor among the at least one joint motor in the object acquisition weight detection for a specified number of consecutive times is greater than the corresponding safety weight threshold, it is determined that the robotic arm is in the abnormal working state; otherwise, it is determined that the robotic arm is in a normal working state.

[0065] In a second aspect, an embodiment of the present application provides a robot arm control device, comprising:

[0066] A robot arm working parameter acquisition unit, used to acquire working parameters of the robot arm of the self-moving cleaning device;

[0067] The robot arm working state determining unit is used to determine the working state of the robot arm based on the working parameters.

[0068] In one embodiment of the present application, optionally, the robot arm working parameter acquisition unit includes:

[0069] The first execution unit is used to obtain working parameters of the mechanical arm of the self-moving cleaning device when performing an object acquisition action, wherein the object acquisition action includes at least one of clamping, grabbing, and lifting.

[0070] In one embodiment of the present application, optionally, the robot arm working parameter acquisition unit includes:

[0071] The second execution unit is used to obtain the working parameters of the robot arm of the self-moving cleaning device when the robot arm does not perform the object acquisition action.

[0072] In one embodiment of the present application, optionally, the working parameters are acquired in real time.

[0073] In one embodiment of the present application, optionally, the robot arm working parameter acquisition unit includes:

[0074] The fourth execution unit is used to obtain at least one of the quadrature-axis current, arm length, preset calibration coefficient, moment of inertia, angular acceleration and friction torque of at least one joint motor of the robotic arm, wherein the preset calibration coefficient is used to reflect the proportional relationship between the quadrature-axis current and the output torque in the at least one joint motor.

[0075] In one embodiment of the present application, optionally, the manner in which the robot arm working parameter acquisition unit acquires the quadrature-axis current of at least one joint motor of the robot arm includes:

[0076] The three-phase current of the at least one joint motor is collected, and the three-phase current is subjected to a Clark transformation to obtain the quadrature-axis current corresponding to the at least one joint motor.

[0077] In one embodiment of the present application, optionally, the manner in which the robot arm working parameter acquisition unit acquires the arm length of at least one joint motor of the robot arm includes:

[0078] For each joint motor of at least one joint motor of the robotic arm, the force arm length of the joint motor is determined as:

[0079]

[0080] Wherein, r represents the current arm length of the joint motor, n is the number of arm segments from the last arm segment of the robot arm to the current arm segment corresponding to the current joint motor, i represents the arm segment number, i∈[1,n], wherein the arm segment number of the last arm segment is 1, the arm segment number of the current arm segment is n, l i represents the arm length from the last arm section to the i-th arm section in the current arm section, θ i represents the angle between the i-th arm segment and the plane where the self-moving cleaning device is located.

[0081] In one embodiment of the present application, optionally, the device further includes:

[0082] An angle determination unit, configured to determine θ if the current arm segment is the first arm segment of the robot arm closest to the self-moving cleaning device. i is the angle between the first arm section and the plane where the self-moving cleaning device is located; if the current arm section is not the first arm section, θ i =θ i+1 -μ i , where μ i represents the offset angle of the i-th arm segment relative to the i+1-th arm segment.

[0083] In one embodiment of the present application, optionally, the robot arm working state determination unit is used to: determine the weight of the object when the robot arm performs an object acquisition action based on the working parameters.

[0084] In one embodiment of the present application, optionally, the robot arm working state determination unit includes:

[0085] an object acquisition weight determination unit, which determines the object acquisition weight of the at least one joint motor based on the working parameters;

[0086] The working state determination unit is used to determine the working state of the at least one joint motor of the robotic arm based on the object acquired weight of the at least one joint motor.

[0087] In one embodiment of the present application, optionally, the object weight determination unit includes:

[0088] The fifth execution unit is used to determine, for each joint motor of the at least one joint motor, a ratio of the product of the quadrature-axis current of the joint motor and the preset calibration coefficient to the lever arm length, as the object weight of the joint motor.

[0089] In one embodiment of the present application, optionally, the object weight determination unit includes:

[0090] The sixth execution unit is used to determine the object acquisition weight of at least one joint motor of the robot arm based on the quadrature axis current, the arm length, the preset calibration coefficient, the moment of inertia, the angular acceleration and the friction torque of at least one joint motor of the robot arm, wherein:

[0091]

[0092] W represents the weight of the object obtained by a single joint motor, I q is the quadrature axis current of a single joint motor, r is the arm length of the arm segment directly driven by the single joint motor, K is the preset calibration coefficient of the single joint motor, α is the angular acceleration of the arm segment directly driven by the single joint motor, j is the moment of inertia of the joint where the single joint motor is located, F f It is the friction torque in the movement of the arm section directly driven by a single joint motor.

[0093] In one embodiment of the present application, optionally, the working state determination unit is used to:

[0094] If the object acquisition weight of any one of the at least one joint motors is greater than the safety weight threshold, it is determined that the robotic arm is in an abnormal working state, otherwise, it is determined that the robotic arm is in a normal working state; or if the object acquisition weight of any one of the at least one joint motors in the object acquisition weight detection is greater than the safety weight threshold for a consecutive specified number of times, it is determined that the robotic arm is in an abnormal working state, otherwise, it is determined that the robotic arm is in a normal working state.

[0095] In one embodiment of the present application, optionally, the device further includes:

[0096] a sixth execution unit, configured to generate a stop object acquisition instruction if it is determined that the robot arm is in an abnormal working state, and control the robot arm to cancel the object acquisition action based on the stop object acquisition instruction;

[0097] The overweight alarm unit is used to generate overweight alarm information.

[0098] In one embodiment of the present application, optionally, the device further includes:

[0099] A target position determination unit, used to determine a target position of an object to be acquired required for the object acquisition action before the robot arm working parameter acquisition unit acquires the working parameters;

[0100] The grasping posture setting unit is used to set the current posture of the robot arm as the grasping posture for the target position.

[0101] In one embodiment of the present application, optionally, the device further includes:

[0102] The object identification unit to be acquired is used to identify the object to be acquired through an object identification device before the target position determination unit determines the target position, wherein the object identification device includes at least one of a visual sensor, a laser sensor, an ultrasonic sensor, and an infrared sensor.

[0103] In one embodiment of the present application, optionally, the grasping posture setting unit is used to:

[0104] Based on the target position, determine the posture configuration information of the robot arm when it is in the grasping posture, wherein the posture configuration information includes:

[0105] The angle between the first arm segment of the mechanical arm closest to the self-moving cleaning device and the plane where the self-moving cleaning device is located;

[0106] An offset angle of each arm segment other than the first arm segment in the robotic arm relative to the preceding arm segment in the direction adjacent to the first arm segment; and

[0107] The arm length of each arm section in the robotic arm.

[0108] In one embodiment of the present application, optionally, the device further includes:

[0109] A robot arm initial detection unit is used to detect whether each joint motor of the robot arm is in a valid working state in response to a startup instruction for the robot arm before the robot arm working parameter acquisition unit acquires the working parameters, wherein if each joint motor of the robot arm is in a valid working state, the robot arm working parameter acquisition unit is allowed to acquire the working parameters.

[0110] In one embodiment of the present application, optionally, the device further includes:

[0111] The weighing posture adjustment unit is used to adjust the robotic arm from the grasping posture to the weighing posture after the grasping posture setting unit sets the current posture of the robotic arm to the grasping posture for the target position.

[0112] In one embodiment of the present application, optionally, the robot arm working parameter acquisition unit includes:

[0113] an adjustment process monitoring unit, configured to monitor the working parameters of the robotic arm in real time during the adjustment process of adjusting the robotic arm from the grasping posture to the weighing posture, so as to determine the working state of the robotic arm based on the working parameters;

[0114] a sixth execution unit, configured to interrupt the adjustment process and execute an overweight protection strategy if the working state of the robot arm is an abnormal working state;

[0115] The seventh execution unit is used to continue the adjustment process if the working state of the robot arm is a normal working state.

[0116] In one embodiment of the present application, optionally, the robot arm working state determination unit is used to:

[0117] If the object acquisition weight of any one of the at least one joint motors is greater than the corresponding safety weight threshold, it is determined that the robotic arm is in the abnormal working state; otherwise, it is determined that the robotic arm is in the normal working state; or if the object acquisition weight of any one of the at least one joint motors in the object acquisition weight detection is greater than the corresponding safety weight threshold, it is determined that the robotic arm is in the abnormal working state; otherwise, it is determined that the robotic arm is in the normal working state.

[0118] In a third aspect, an embodiment of the present application provides a self-moving cleaning device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are configured to execute any of the methods described in the first aspect above.

[0119] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium storing computer-executable instructions, wherein the computer-executable instructions are used to execute the method described in the first aspect above.

[0120] The above technical solution aims to solve the technical problem that it is difficult to effectively identify the abnormal working state of the robot arm in the related technology, which makes the robot arm easy to be damaged. The working parameters of the robot arm of the self-moving cleaning device are used to determine the current working state of the robot arm, that is, to reversely infer whether the robot arm is in an unsafe working state based on the specific performance of the current working state of the robot arm, so as to facilitate timely identification of the situation of the robot arm carrying overweight objects in the actual scene of the robot arm carrying overweight objects and take countermeasures. Through this technical solution, the robot arm can be prevented from carrying overweight objects for a long time, which increases the flexibility and safety of the robot arm's work, helps to improve the overall performance of the self-moving cleaning equipment, and improves the user experience.

Brief Description of the Drawings

[0121] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0122] Figure 1 A flow chart of a method for controlling a robotic arm according to an embodiment of the present application is shown;

[0123] Figure 2 A flowchart of a robot arm control method according to another embodiment of the present application is shown;

[0124] Figure 3 A schematic diagram of the structure of a mechanical arm according to an embodiment of the present application is shown;

[0125] Figure 4 A flowchart of a robot arm control method according to another embodiment of the present application is shown;

[0126] Figure 5 A flowchart of a robot arm control method according to another embodiment of the present application is shown;

[0127] Figure 6 A block diagram of a robot arm control device according to an embodiment of the present application is shown;

[0128] Figure 7 A block diagram of a self-moving cleaning device according to an embodiment of the present application is shown. [Specific implementation method]

[0129] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0130] Figure 1 A flow chart of a robot arm control method according to an embodiment of the present application is shown.

[0131] like Figure 1 As shown, a robot arm control method according to an embodiment of the present application includes:

[0132] Step 102, obtaining the working parameters of the robot arm of the self-moving cleaning device.

[0133] The work content of the robotic arm of the self-mobile cleaning equipment includes but is not limited to assisting the self-mobile cleaning equipment to cross obstacles, organize items, sort garbage, and handle large volumes of garbage. Its working parameters refer to the parameter configuration of the robotic arm during the execution of these tasks. It can be understood that the working parameters of the robotic arm reflect the performance of the robotic arm in the current working state.

[0134] In a possible design, the operating parameters include quadrature-axis current, lever arm length, and a preset calibration coefficient.

[0135] In another possible design, the operating parameters include quadrature-axis current, lever arm length, preset calibration coefficient, moment of inertia, angular acceleration and friction torque.

[0136] Therefore, more specifically, the working parameters of the robotic arm reflect the performance of the robotic arm under the influence of its actual load-bearing content in the current working state.

[0137] In a possible design, step 102 includes: obtaining working parameters of the robotic arm of the self-mobile cleaning device when performing an object acquisition action.

[0138] At this time, the actual load content of the robot arm in the current working state is the object to be acquired by performing the object acquisition action. When the robot arm of the self-moving cleaning device performs the object acquisition action, it may face the situation that the acquired object is overweight, which may cause the self-moving cleaning device to be in an unsafe working state. In other words, the working parameters of the robot arm when performing the object acquisition action are the specific manifestation of the current working state of the robot arm.

[0139] The object acquisition action includes at least one of clamping, grabbing, and lifting.

[0140] Optionally, the robotic arm has at least one clamp for clamping an object.

[0141] Optionally, the robotic arm has at least one gripper for grasping an object.

[0142] Optionally, the robotic arm has at least one shovel for scooping up objects and then lifting the objects.

[0143] In a possible design, the clamp, the gripper or the shovel can be arranged at the end of any arm section of the robot arm. Optionally, the clamp, the gripper or the shovel is arranged at the end of the last arm section farthest from the self-moving cleaning device in the robot arm.

[0144] In a possible design, step 102 includes: obtaining working parameters of the robot arm of the self-moving cleaning device when the robot arm does not perform an object acquisition action.

[0145] When the robotic arm is not performing the object acquisition action, the self-moving cleaning device may be in a standby state, or it may be in a working state where the robotic arm is not in use. At this time, although the robotic arm has not performed the object acquisition action, it may still face the situation where the acquired items are overweight. For example, the user may hang other items on the robotic arm, such as decorations, daily necessities, etc. For another example, when the self-moving cleaning device is moving, or when the robotic arm has previously performed the object acquisition action, it may cause the robotic arm to be entangled, hooked, or set, causing the actual weight of the item to act on the robotic arm. It can be understood that at this time, the actual load content of the robotic arm in the current working state is empty, or it is an object that was passively carried when the object acquisition action was previously performed.

[0146] The above situations may cause the self-propelled cleaning device to be in an unsafe working state. Since the working parameters of the robot arm when it is not performing the object acquisition action are the specific manifestation of the current working state of the robot arm, the working parameters of the robot arm when it is not performing the object acquisition action can be used to determine the current working state of the robot arm, so as to effectively identify whether the robot arm is in an unsafe working state.

[0147] Step 104: Determine the working state of the robot arm based on the working parameters.

[0148] Since the working parameters of the robot arm can reflect the performance of the robot arm in the current working state under the influence of its actual load-bearing content, the current working state of the robot arm can be inferred based on this performance.

[0149] The above technical solution determines the current working state of the robot arm through the working parameters of the robot arm of the self-moving cleaning device, that is, based on the specific performance of the current working state of the robot arm, it is inferred whether the robot arm is in an unsafe working state, which is convenient for timely identifying the situation of the robot arm overloading objects in the actual scene of the robot arm overloading objects and taking countermeasures. Through this technical solution, the overweight operation of the robot arm can be interrupted in time to avoid the robot arm carrying overweight objects for a long time, which increases the flexibility and safety of the robot arm's work, helps to improve the overall performance of the self-moving cleaning equipment, and improves the user experience.

[0150] In one possible design, step 104 includes: when determining the working state of the robotic arm, the object acquisition weight of the at least one joint motor can be determined based on the working parameters; and then based on the object acquisition weight of the at least one joint motor, the working state of the at least one joint motor of the robotic arm is determined.

[0151] The object acquisition weight described here refers to the overall load capacity of the current arm segment directly driven by the joint motor. In a possible design, the object acquisition weight of a single joint motor is the sum of the weight of all arm segments from the current arm segment directly driven by the joint motor to the end arm segment of the robotic arm closest to the object to be acquired and the weight of the object to be acquired.

[0152] Therefore, the working states of several joint motors in the robotic arm can be used to reflect whether the robotic arm is carrying an overweight object, or in other words, whether the robotic arm is in an unsafe working state for carrying an overweight object.

[0153] In one possible design, step 104 includes: based on the working parameters, determining the weight of the object when the robotic arm performs the object acquisition action. The weight of the object when the robotic arm performs the object acquisition action is the effective load-bearing capacity of the robotic arm when performing the object acquisition action, and the effective load-bearing capacity can reflect the carrying capacity of the robotic arm for the acquired content. Optionally, if this effective load-bearing capacity exceeds the maximum effective load-bearing capacity that the robotic arm can bear, it can be determined that the robotic arm is in an unsafe working state of overweight objects. Therefore, the weight of the object when the robotic arm performs the object acquisition action can also serve as an effective basis for identifying the working state of the robotic arm.

[0154] Optionally, for any joint motor, the weight of all arm sections from the current arm section directly driven by the joint motor to the end arm section of the robotic arm close to the object to be acquired can be obtained, and the difference between the object acquisition weight corresponding to the joint motor and the weight of all arm sections can be determined as the weight of the object when the robotic arm performs the object acquisition action.

[0155] The object acquisition weight when the robot arm performs the object acquisition action reflects the actual load-bearing level of the robot arm as a whole. The actual load-bearing level can reflect to a certain extent whether the robot arm has an overweight object, or in other words, the actual load-bearing level can reflect to a certain extent whether the robot arm is in an unsafe working state of overweight objects. Therefore, the object acquisition weight when the robot arm performs the object acquisition action can be used as an effective basis for identifying the working state of the robot arm.

[0156] The following is a detailed description of the technical solution of the present application by combining two methods of calculating the weight of an object using joint motors.

[0157] exist Figure 1 Based on the illustrated embodiment, Figure 2 A flow chart of a robot arm control method according to another embodiment of the present application is shown.

[0158] like Figure 2 As shown, a robot arm control method according to another embodiment of the present application includes:

[0159] Step 202, obtaining the quadrature-axis current, the lever arm length, and the preset calibration coefficient of at least one joint motor of the robot arm.

[0160] In one possible design, the quadrature axis current of at least one joint motor of the robot arm is obtained by collecting the three-phase current of the at least one joint motor and performing a Clark transformation on the three-phase current to obtain the quadrature axis current corresponding to the at least one joint motor. To a certain extent, the quadrature axis current of the joint motor can be regarded as the performance of the output torque of the joint motor in the current dimension.

[0161] The preset calibration coefficient is used to reflect the proportional relationship between the quadrature axis current and the output torque in the at least one joint motor. Specifically, in the production process of each joint motor, the ratio of the test quadrature axis current and the test output torque corresponding to each load can be measured by loading multiple loads respectively, and finally, the preset calibration coefficient corresponding to the joint motor is determined by the ratio of the multiple loads. The preset calibration coefficient of each joint motor is stored in the controller of the joint motor or the central processor of the self-moving cleaning device to which the joint motor belongs, so as to be called when calculating the weight of the object obtained by the joint motor.

[0162] Optionally, the average value of the ratios of the multiple loads is set as a preset calibration coefficient corresponding to the joint motor.

[0163] In a possible design, the method of obtaining the arm length of the at least one joint motor of the robotic arm is as follows: for each joint motor of the at least one joint motor of the robotic arm, the arm length of the joint motor is determined as:

[0164]

[0165] Wherein, r represents the current arm length of the joint motor, n is the number of arm segments from the last arm segment of the robot arm to the current arm segment corresponding to the current joint motor, i represents the arm segment number, i∈[1,n], wherein the arm segment number of the last arm segment is 1, the arm segment number of the current arm segment is n, l i represents the arm length from the last arm section to the i-th arm section in the current arm section, θ i represents the angle between the i-th arm segment and the plane where the self-moving cleaning device is located. If the current arm segment is the first arm segment of the robot arm closest to the self-moving cleaning device, determine θ i is the angle between the first arm section and the plane where the self-moving cleaning device is located. If the current arm section is not the first arm section, θ i =θ i+1 -μ i , where μ i represents the offset angle of the i-th arm segment relative to the i+1-th arm segment.

[0166] Combining the above content and Figure 3 As shown, if the self-mobile cleaning device includes a first arm section away from the main body of the self-mobile cleaning device and a second arm section adjacent to the main body of the self-mobile cleaning device, the first arm section is controlled by a first joint motor, and the second arm section is controlled by a second joint motor, then the angle between the second arm section and the plane where the self-mobile cleaning device is located is the known quantity A in the posture configuration information when the robot arm is in the grasping posture, and the offset angle of the first arm section relative to the direction of the second arm section is the known quantity B in the posture configuration information, then the angle between the first arm section and the plane where the self-mobile cleaning device is located is AB.

[0167] On this basis, the arm length of the first joint motor is actually equivalent to Figure 3 The x segment shown is the first product of the length L1 of the first arm segment and cos(AB). The length of the force arm of the second joint motor is actually equivalent to Figure 3 The sum of the x segment and the y segment is shown, wherein the x segment is the second product of the length L2 of the second arm segment and cosA, and the sum of the x segment and the y segment is the sum of the first product and the second product.

[0168] Of course, the number of arm segments of the robot arm of the self-moving cleaning device can be any number that meets the actual object acquisition requirements, and is not limited to Figure 3 The two sections shown.

[0169] Step 204 , determining the object acquisition weight of at least one joint motor of the robot arm based on the quadrature-axis current, the lever arm length, and a preset calibration coefficient of at least one joint motor of the robot arm.

[0170] The cross-axis current, lever arm length and preset calibration coefficient of any joint motor each reflect the load-bearing capacity of the joint motor in different dimensions. Therefore, the actual weight weighed by the joint motor can be determined based on the three, that is, the weight borne by the arm section directly driven by the joint motor when the robotic arm acquires an object, that is, the weight of the object acquired.

[0171] In a possible design, for each of the at least one joint motor, the ratio of the product of the quadrature-axis current of the joint motor and the preset calibration coefficient to the lever arm length is determined to obtain the weight of the object of the joint motor.

[0172] Specifically, when the robot arm grabs an object, the joint motor needs to overcome additional resistance to do work. At this time, the current will increase and is proportional to the quadrature axis current. The output torque of the joint motor is calculated as follows:

[0173] T e =K×I q ,

[0174] Among them, T e Represents the output torque of the joint motor, K is the preset calibration coefficient of the joint motor, I q It is the q-axis current value after the joint motor is decoupled, that is, the quadrature-axis current of the joint motor.

[0175] When the robot arm grabs the object, its load torque can be expressed as:

[0176] T l =α*j+F f +T g ,

[0177] Where α is the angular acceleration of the arm segment directly driven by the joint motor, j is the moment of inertia of the joint where the joint motor is located, and F f is the friction torque in the arm joint motion directly driven by the joint motor, T g It is the weight of the object captured by the robot and the arm joint itself. When the robot is in a steady state (stationary or uniform motion), the output torque T of the joint motor e and load torque T l Equal, that is:

[0178] K*I q =α*j+F f +T g .

[0179] Furthermore, T g=W*r, W is the weight of the object obtained by the joint motor, r is the length of the arm arm directly driven by the joint motor, from which it can be inferred that the calculation method of the weight of the object obtained by the joint motor is as follows:

[0180]

[0181] On this basis, if the influence of angular acceleration and friction torque is ignored, that is, angular acceleration and friction torque are set to zero, the calculation method of the object weight obtained by the joint motor is as follows:

[0182]

[0183] That is, the object weight acquired by the joint motor is the ratio of the product of the quadrature-axis current of the joint motor and the preset calibration coefficient to the length of the lever arm.

[0184] Step 206 : Determine the working state of the at least one joint motor of the robotic arm based on the object acquired weight of the at least one joint motor.

[0185] For a single joint motor, its object acquisition weight is the weight it bears when acquiring an object, or in other words, the object acquisition weight of the joint motor reflects the actual load situation of the joint motor when acquiring an object, and this actual complex situation is the characteristic performance of the working state of the joint motor. Therefore, the working state of the joint motor can be determined based on the object acquisition weight of the joint motor.

[0186] The above technical solution calculates the actual load of the joint motor when acquiring an object through the cross-axis current of the joint motor, the length of the lever arm and the preset calibration coefficient, which is used as the basis for judging the working state of the joint motor, so as to facilitate timely identification of the situation of the robot arm carrying an overweight object in the actual scene of the robot arm carrying an overweight object and take countermeasures. Through this technical solution, the robot arm can be prevented from carrying an overweight object for a long time, which increases the flexibility and safety of the robot arm's work, helps to improve the overall performance of the self-moving cleaning equipment, and enhances the user experience.

[0187] exist Figure 2 Based on the illustrated embodiment, Figure 4 A flow chart of a robot arm control method according to yet another embodiment of the present application is shown.

[0188] like Figure 4 As shown, a robot arm control method according to another embodiment of the present application includes:

[0189] Step 402, obtaining the quadrature-axis current, lever arm length, preset calibration coefficient, moment of inertia, angular acceleration and friction torque of at least one joint motor of the robotic arm.

[0190] Step 404, based on the quadrature axis current, arm length, preset calibration coefficient, moment of inertia, angular acceleration and friction torque of at least one joint motor of the robot arm, determine the object acquisition weight of the at least one joint motor, wherein:

[0191]

[0192] W represents the weight of the object obtained by a single joint motor, I q is the quadrature axis current of a single joint motor, r is the arm length of the arm segment directly driven by the single joint motor, K is the preset calibration coefficient of the single joint motor, α is the angular acceleration of the arm segment directly driven by the single joint motor, j is the moment of inertia of the joint where the single joint motor is located, F f It is the friction torque in the movement of the arm section directly driven by a single joint motor.

[0193] Step 406 : Determine the working state of the at least one joint motor of the robotic arm based on the object acquired weight of the at least one joint motor.

[0194] In the above technical scheme, the influence of moment of inertia, angular acceleration and friction torque are taken into account when calculating the weight of an object, which can more accurately calculate the actual load-bearing capacity of the joint motor, thereby facilitating accurate determination of the working state of the joint motor and achieving more accurate identification of the situation in which the robotic arm is carrying overweight objects in actual scenarios where the robotic arm is carrying overweight objects.

[0195] in addition, Figure 4 The derivation process of the calculation formula for obtaining the weight of the object in the embodiment shown has been Figure 2 The above is described in the embodiment shown in the figure and will not be described in detail here.

[0196] Of course, in a possible design, any number of information of the quadrature-axis current, arm length, preset calibration coefficient, moment of inertia, angular acceleration and friction torque of at least one joint motor of the robotic arm can be obtained as a basis for determining the working state of the robotic arm, and is not limited to Figure 2 and Figure 4 The example given.

[0197] exist Figure 2 and Figure 4 Based on the illustrated embodiment, optionally, the working state of at least one joint motor of the robotic arm is determined as follows: if the object acquired by any one of the at least one joint motors is greater than a safety weight threshold, it is determined that the robotic arm is in an abnormal working state; otherwise, it is determined that the robotic arm is in a normal working state.

[0198] Each joint motor corresponds to a safety weight threshold, which reflects the maximum weight load capacity of the corresponding joint motor when acquiring an object without overweight. On this basis, in at least one joint motor of the robotic arm, as long as the weight of the object acquired by any joint motor is greater than the safety weight threshold, it means that the current weight load capacity of the joint motor exceeds its maximum weight load capacity when it is not overweight, and it can be determined that the joint motor is overweight, causing the robotic arm to be in an abnormal working state.

[0199] exist Figure 2 and Figure 4 Based on the illustrated embodiment, optionally, the working state of the at least one joint motor of the robotic arm is determined as follows: if the object acquisition weight of any one of the at least one joint motors in the object acquisition weight detection for a specified number of consecutive times is greater than a safety weight threshold, it is determined that the robotic arm is in an abnormal working state; otherwise, it is determined that the robotic arm is in a normal working state.

[0200] Each joint motor corresponds to a safety weight threshold, which reflects the maximum weight load capacity of the corresponding joint motor when acquiring an object without overweight. On this basis, in at least one joint motor of the robotic arm, as long as the weight of the object acquired by any joint motor for a specified number of consecutive times is greater than the safety weight threshold, it means that the current weight load capacity of the joint motor has continuously exceeded its maximum weight load capacity without overweight during the specified number of consecutive detections. At this point, it can be determined that the joint motor is overweight, causing the robotic arm to be in an abnormal working state.

[0201] The above technical solutions can effectively identify whether the joint motor is working overload, thereby further effectively determining whether the robotic arm is in an abnormal working state.

[0202] Based on any of the above embodiments, optionally, if it is determined that the robot arm is in an abnormal working state, a stop object acquisition instruction is generated, and based on the stop object acquisition instruction, the robot arm is controlled to cancel the object acquisition action. That is, once the robot arm is in an abnormal working state, the current object acquisition action is no longer executed, and the overload work of the joint motor and the robot arm is terminated in time.

[0203] In addition, when the command to stop acquiring the object is generated, an overweight alarm message is also generated to remind the user to pay attention to the overweight working condition of the robot arm. Optionally, the overweight alarm message includes but is not limited to sending sound information, screen display information, etc. through the self-mobile cleaning device and / or other electronic devices connected to the self-mobile cleaning device.

[0204] In addition, based on any of the above embodiments, any working parameters are acquired in real time, that is, the working parameters are directly acquired during the real-time operation of the self-mobile cleaning device, so as to timely, quickly and effectively identify the working status of the robot arm in real time.

[0205] Figure 5 A flow chart of a robot arm control method according to yet another embodiment of the present application is shown.

[0206] like Figure 5 As shown, a robot arm control method according to another embodiment of the present application includes:

[0207] Step 502: In response to a start instruction for a robot arm of a self-moving cleaning device, detecting whether each joint motor of the robot arm is in an effective working state.

[0208] Among them, the joint motor is in an effective working state, which means that the joint motor can operate normally and has the ability to drive the arm sections. If each joint motor of the robotic arm is in an effective working state, it means that the robotic arm has the ability to normally acquire objects. On this basis, the working state of the robotic arm can be further detected.

[0209] Step 504: If each joint motor of the robotic arm is in an effective working state, the object to be obtained is identified by an object identification device.

[0210] Before acquiring an object, it is first necessary to identify the object to be acquired so that further operations such as grasping, clamping, and pushing can be performed on the object to be acquired.

[0211] The object recognition device includes at least one of a visual sensor, a laser sensor, an ultrasonic sensor, and an infrared sensor. Of course, the object recognition device can also be any other device that meets the actual object recognition requirements, and is not limited to the above examples.

[0212] Step 506: determine the target position of the object to be acquired required for the object acquisition action, and set the current posture of the robot arm as the grasping posture for the target position.

[0213] After identifying the object to be acquired, the relative position of the object to be acquired and the self-moving cleaning device can be identified by a sensor with a ranging function as the target position, and with respect to the target position, the current posture of the robotic arm is transformed through mechanical action movement into a grasping posture that can grasp the object to be acquired at the target position.

[0214] Optionally, in the process of changing the current posture of the robot arm, the self-moving cleaning device can be driven to move toward the object to be acquired at the same time, so that the self-moving cleaning device moves to a position where its own robot arm can effectively acquire the object to be acquired.

[0215] When setting the grasping posture, the posture configuration information of the mechanical arm when in the grasping posture can be determined based on the target position, that is, the posture configuration information of each arm section of the mechanical arm is determined by the relative position between the target position and the self-moving cleaning device.

[0216] The posture configuration information includes: the angle between the first arm segment closest to the self-moving cleaning device in the robotic arm and the plane where the self-moving cleaning device is located; the offset angle of each arm segment other than the first arm segment in the robotic arm relative to the preceding arm segment in the direction of the first arm segment; and the arm length of each arm segment in the robotic arm. Based on the aforementioned angle, offset angle and arm length, the relative position relationship of each arm segment can be determined, thereby determining the grasping posture of the entire robotic arm.

[0217] Step 508: adjusting the robotic arm from the grasping posture to the weighing posture.

[0218] It can be understood that the grasping posture is the posture corresponding to when the robot arm is in a position to grasp the object to be grasped. In the grasping posture, the robot arm does not attempt to grasp the object to be grasped.

[0219] The weighing posture is the posture of the robot arm when it tries to grab the object to be grabbed, causing its displacement to change. This process is very short. It is the initial short time for the robot arm to try to grab the object to be grabbed after posing the grasping posture for the object to be grabbed. During this process, the displacement of the object to be grabbed is very small.

[0220] Further, step 508 may be understood as starting the action of adjusting the robot arm from the grasping posture to the weighing posture.

[0221] Step 510 , during the adjustment process of adjusting the robotic arm from the grasping posture to the weighing posture, monitoring the working parameters of the robotic arm in real time to determine the working state of the robotic arm based on the working parameters.

[0222] Step 512: If the working state of the robotic arm is an abnormal working state, the adjustment process is interrupted and an overweight protection strategy is executed; otherwise, if the working state of the robotic arm is a normal working state, the adjustment process is continued.

[0223] That is to say, during the short period of time when the robotic arm attempts to acquire the object after it has assumed a grasping posture, the working status of the robotic arm is monitored in real time. Once the working status of the robotic arm is abnormal, the process of acquiring the object is interrupted and the overweight protection strategy is executed.

[0224] Optionally, the overweight protection strategy includes generating an overweight alarm message or any other operation that can prompt the user to pay attention to the behavior of the robotic arm.

[0225] Optionally, the overweight protection strategy includes any operation that interrupts the overweight working behavior of the robotic arm, such as commanding the robotic arm to be empty, retracting the robotic arm, etc.

[0226] Further, if the object acquisition weight of any one of the at least one joint motors is greater than the corresponding safety weight threshold, it is determined that the robot arm is in the abnormal working state, otherwise, it is determined that the robot arm is in a normal working state; or if the object acquisition weight of any one of the at least one joint motors in the object acquisition weight detection for a specified number of consecutive times is greater than the corresponding safety weight threshold, it is determined that the robot arm is in the abnormal working state, otherwise, it is determined that the robot arm is in a normal working state. This solution has been described in the previous text and will not be repeated here.

[0227] The above technical solution can detect the working capacity level of the robot arm of the self-mobile cleaning device before and after the robot arm is started and during the adjustment process from the grasping posture to the weighing posture, so as to timely identify the insufficient working capacity of the robot arm in various robot arm working scenes, and in particular, accurately identify the situation where the robot arm is overloaded and take countermeasures. Through this technical solution, the overweight operation of the robot arm can be interrupted in time to avoid the robot arm from carrying overweight objects for a long time, which increases the flexibility and safety of the robot arm's work, helps to improve the overall performance of the self-mobile cleaning device, and improves the user experience.

[0228] Figure 6 A block diagram of a robot arm control device according to an embodiment of the present application is shown.

[0229] like Figure 6 As shown, the embodiment of the present application provides a robot arm control device 600, including:

[0230] A robot arm working parameter acquisition unit 602 is used to acquire working parameters of the robot arm of the self-moving cleaning device;

[0231] The robot arm working state determining unit 604 is used to determine the working state of the robot arm based on the working parameters.

[0232] In one embodiment of the present application, optionally, the robot arm working parameter acquisition unit 602 includes:

[0233] The first execution unit is used to obtain working parameters of the mechanical arm of the self-moving cleaning device when performing an object acquisition action, wherein the object acquisition action includes at least one of clamping, grabbing, and lifting.

[0234] In one embodiment of the present application, optionally, the robot arm working parameter acquisition unit 602 includes:

[0235] The second execution unit is used to obtain the working parameters of the robot arm of the self-moving cleaning device when the robot arm does not perform the object acquisition action.

[0236] In one embodiment of the present application, optionally, the working parameters are acquired in real time.

[0237] In one embodiment of the present application, optionally, the robot arm working parameter acquisition unit 602 includes:

[0238] The fourth execution unit is used to obtain at least one of the quadrature-axis current, arm length, preset calibration coefficient, moment of inertia, angular acceleration and friction torque of at least one joint motor of the robotic arm, wherein the preset calibration coefficient is used to reflect the proportional relationship between the quadrature-axis current and the output torque in the at least one joint motor.

[0239] In one embodiment of the present application, optionally, the manner in which the robot arm working parameter acquisition unit 602 acquires the quadrature-axis current of at least one joint motor of the robot arm includes:

[0240] The three-phase current of the at least one joint motor is collected, and the three-phase current is subjected to a Clark transformation to obtain the quadrature-axis current corresponding to the at least one joint motor.

[0241] In one embodiment of the present application, optionally, the manner in which the robot arm working parameter acquisition unit 602 acquires the arm length of at least one joint motor of the robot arm includes:

[0242] For each joint motor of at least one joint motor of the robotic arm, the force arm length of the joint motor is determined as:

[0243]

[0244] Wherein, r represents the current arm length of the joint motor, n is the number of arm segments from the last arm segment of the robot arm to the current arm segment corresponding to the current joint motor, i represents the arm segment number, i∈[1,n], wherein the arm segment number of the last arm segment is 1, the arm segment number of the current arm segment is n, l i represents the arm length from the last arm section to the i-th arm section in the current arm section, θ i represents the angle between the i-th arm segment and the plane where the self-moving cleaning device is located.

[0245] In one embodiment of the present application, optionally, the robot arm control device 600 further includes:

[0246] An angle determination unit, configured to determine θ if the current arm segment is the first arm segment of the robot arm closest to the self-moving cleaning device. i is the angle between the first arm section and the plane where the self-moving cleaning device is located; if the current arm section is not the first arm section, θ i =θ i+1 -μ i , where μ i represents the offset angle of the i-th arm segment relative to the i+1-th arm segment.

[0247] In one embodiment of the present application, optionally, the robot arm working state determination unit 604 is used to: determine the weight of the object when the robot arm performs the object acquisition action based on the working parameters.

[0248] In one embodiment of the present application, optionally, the robot arm working state determination unit 604 includes:

[0249] an object acquisition weight determination unit, which determines the object acquisition weight of the at least one joint motor based on the working parameters;

[0250] The working state determination unit is used to determine the working state of the at least one joint motor of the robotic arm based on the object acquired weight of the at least one joint motor.

[0251] In one embodiment of the present application, optionally, the object weight determination unit includes:

[0252] The fifth execution unit is used to determine, for each joint motor of the at least one joint motor, a ratio of the product of the quadrature-axis current of the joint motor and the preset calibration coefficient to the lever arm length, as the object weight of the joint motor.

[0253] In one embodiment of the present application, optionally, the object weight determination unit includes:

[0254] The sixth execution unit is used to determine the object acquisition weight of at least one joint motor of the robot arm based on the quadrature axis current, the arm length, the preset calibration coefficient, the moment of inertia, the angular acceleration and the friction torque of at least one joint motor of the robot arm, wherein:

[0255]

[0256] W represents the weight of the object obtained by a single joint motor, I qis the quadrature axis current of a single joint motor, r is the arm length of the arm segment directly driven by the single joint motor, K is the preset calibration coefficient of the single joint motor, α is the angular acceleration of the arm segment directly driven by the single joint motor, j is the moment of inertia of the joint where the single joint motor is located, F f It is the friction torque in the movement of the arm section directly driven by a single joint motor.

[0257] In one embodiment of the present application, optionally, the working state determination unit is used to:

[0258] If the object acquisition weight of any one of the at least one joint motors is greater than the safety weight threshold, it is determined that the robotic arm is in an abnormal working state, otherwise, it is determined that the robotic arm is in a normal working state; or if the object acquisition weight of any one of the at least one joint motors in the object acquisition weight detection is greater than the safety weight threshold for a consecutive specified number of times, it is determined that the robotic arm is in an abnormal working state, otherwise, it is determined that the robotic arm is in a normal working state.

[0259] In one embodiment of the present application, optionally, the robot arm control device 600 further includes:

[0260] a sixth execution unit, configured to generate a stop object acquisition instruction if it is determined that the robot arm is in an abnormal working state, and control the robot arm to cancel the object acquisition action based on the stop object acquisition instruction;

[0261] The overweight alarm unit is used to generate overweight alarm information.

[0262] In one embodiment of the present application, optionally, the robot arm control device 600 further includes:

[0263] A target position determination unit, used to determine the target position of the object to be acquired required for the object acquisition action before the robot arm working parameter acquisition unit 602 acquires the working parameters;

[0264] The grasping posture setting unit is used to set the current posture of the robot arm as the grasping posture for the target position.

[0265] In one embodiment of the present application, optionally, the robot arm control device 600 further includes:

[0266] The object identification unit to be acquired is used to identify the object to be acquired through an object identification device before the target position determination unit determines the target position, wherein the object identification device includes at least one of a visual sensor, a laser sensor, an ultrasonic sensor, and an infrared sensor.

[0267] In one embodiment of the present application, optionally, the grasping posture setting unit is used to:

[0268] Based on the target position, determine the posture configuration information of the robot arm when it is in the grasping posture, wherein the posture configuration information includes:

[0269] The angle between the first arm segment of the mechanical arm closest to the self-moving cleaning device and the plane where the self-moving cleaning device is located;

[0270] An offset angle of each arm segment other than the first arm segment in the robotic arm relative to the preceding arm segment in the direction adjacent to the first arm segment; and

[0271] The arm length of each arm section in the robotic arm.

[0272] In one embodiment of the present application, optionally, the robot arm control device 600 further includes:

[0273] The robot arm initial detection unit is used to detect whether each joint motor of the robot arm is in a valid working state in response to a startup instruction for the robot arm before the robot arm working parameter acquisition unit 602 acquires the working parameters, wherein if each joint motor of the robot arm is in a valid working state, the robot arm working parameter acquisition unit 602 is allowed to acquire the working parameters.

[0274] In one embodiment of the present application, optionally, the robot arm control device 600 further includes:

[0275] The weighing posture adjustment unit is used to adjust the mechanical arm from the grasping posture to the weighing posture after the grasping posture setting unit sets the current posture of the mechanical arm to the grasping posture for the target position.

[0276] In one embodiment of the present application, optionally, the robot arm working parameter acquisition unit 602 includes:

[0277] an adjustment process monitoring unit, configured to monitor the working parameters of the robotic arm in real time during the adjustment process of adjusting the robotic arm from the grasping posture to the weighing posture, so as to determine the working state of the robotic arm based on the working parameters;

[0278] a sixth execution unit, configured to interrupt the adjustment process and execute an overweight protection strategy if the working state of the robot arm is an abnormal working state;

[0279] The seventh execution unit is used to continue the adjustment process if the working state of the robot arm is a normal working state.

[0280] In one embodiment of the present application, optionally, the robot arm working state determination unit 604 is used to:

[0281] If the object acquisition weight of any one of the at least one joint motors is greater than the corresponding safety weight threshold, it is determined that the robotic arm is in the abnormal working state; otherwise, it is determined that the robotic arm is in the normal working state; or if the object acquisition weight of any one of the at least one joint motors in the object acquisition weight detection is greater than the corresponding safety weight threshold, it is determined that the robotic arm is in the abnormal working state; otherwise, it is determined that the robotic arm is in the normal working state.

[0282] The robot arm control device 600 uses any of the solutions described in the above embodiments, and therefore has all the above technical effects, which will not be repeated here.

[0283] Figure 7 A block diagram of a self-moving cleaning device according to an embodiment of the present application is shown.

[0284] like Figure 7 As shown, a self-moving cleaning device 700 of an embodiment of the present application includes at least one memory 702; and a processor 704 in communication with the at least one memory 702; wherein the memory stores instructions executable by the at least one processor 704, and the instructions are configured to execute the scheme described in any of the above embodiments. Therefore, the self-moving cleaning device 700 has the same technical effects as any of the above embodiments, and will not be described in detail here.

[0285] In addition, an embodiment of the present application provides a computer-readable storage medium storing computer-executable instructions, wherein the computer-executable instructions are used to perform the following steps:

[0286] Obtaining the working parameters of the robot arm of the self-mobile cleaning device;

[0287] Based on the working parameters, the working state of the robotic arm is determined.

[0288] It should be noted that the above functions or steps that can be implemented by the computer-readable storage medium or computer device can refer to the relevant description in the aforementioned method embodiment. In order to avoid repetition, they will not be described one by one here.

[0289] The above describes in detail the technical solution of the present application in combination with the accompanying drawings. Through the technical solution of the present application, the working parameters of the robot arm of the self-moving cleaning device are used to determine the current working state of the robot arm, that is, based on the specific performance of the current working state of the robot arm, it is inferred whether the robot arm is in an unsafe working state, which is convenient for timely identification of the situation of the robot arm overloading objects in the actual scene of the robot arm overloading objects and taking countermeasures. Through this technical solution, the overweight operation of the robot arm can be interrupted in time to avoid the robot arm from carrying overweight objects for a long time, which increases the flexibility and safety of the robot arm's work, helps to improve the overall performance of the self-moving cleaning device, and improves the user experience.

[0290] It should be understood that the term "and / or" used in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0291] It should be understood that although the terms first, second, etc. may be used to describe execution units in the embodiments of the present application, these execution units should not be limited to these terms. These terms are only used to distinguish execution units from each other. For example, without departing from the scope of the embodiments of the present application, the first execution unit may also be referred to as the second execution unit, and similarly, the second execution unit may also be referred to as the first execution unit.

[0292] The word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrases "if it is determined" or "if (stated condition or event) is detected" may be interpreted as "when it is determined" or "in response to determining" or "when detecting (stated condition or event)" or "in response to detecting (stated condition or event)", depending on the context.

[0293] The terms used in the embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to limit the present application. The singular forms "a", "said" and "the" used in the embodiments of the present application and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings.

[0294] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0295] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0296] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0297] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A robot arm control method, characterized in that: include: Obtaining the working parameters of the robot arm of the self-mobile cleaning device; Based on the working parameters, the working state of the robotic arm is determined.

2. The method according to claim 1, characterized in that The working parameters of the robot arm obtained from the mobile cleaning device include: The working parameters of the mechanical arm of the self-moving cleaning device when performing an object acquisition action are obtained, wherein the object acquisition action includes at least one of clamping, grabbing, and lifting.

3. The method according to claim 1, characterized in that The working parameters of the robot arm obtained from the mobile cleaning device include: The working parameters of the robot arm of the self-moving cleaning device when not performing an object acquisition action are obtained.

4. The method according to claim 2 or 3, characterized in that: The working parameters are obtained in real time.

5. The method according to claim 1, characterized in that The working parameters of the robot arm obtained from the mobile cleaning device include: Obtain at least one of the quadrature-axis current, arm length, preset calibration coefficient, moment of inertia, angular acceleration and friction torque of at least one joint motor of the robotic arm, wherein the preset calibration coefficient is used to reflect the proportional relationship between the quadrature-axis current and the output torque in the at least one joint motor.

6. The method according to claim 5, characterized in that The obtaining of the quadrature-axis current of at least one joint motor of the robotic arm comprises: The three-phase current of the at least one joint motor is collected, and the three-phase current is subjected to a Clark transformation to obtain the quadrature-axis current corresponding to the at least one joint motor.

7. The method according to claim 5, characterized in that The obtaining of the arm length of at least one joint motor of the robotic arm comprises: For each joint motor of at least one joint motor of the robotic arm, the force arm length of the joint motor is determined as: Wherein, r represents the current arm length of the joint motor, n is the number of arm segments from the last arm segment of the robot arm to the current arm segment corresponding to the current joint motor, i represents the arm segment number, i∈[1,n], wherein the arm segment number of the last arm segment is 1, the arm segment number of the current arm segment is n, l i represents the arm length from the last arm section to the i-th arm section in the current arm section, θ i represents the angle between the i-th arm segment and the plane where the self-moving cleaning device is located.

8. The method according to claim 7, characterized in that Also includes: If the current arm segment is the first arm segment of the robot arm closest to the self-moving cleaning device, determine θ i is the angle between the first arm section and the plane where the self-propelled cleaning device is located; If the current arm segment is not the first arm segment, θ i =θ i+1 -μ i , where μ i represents the offset angle of the i-th arm segment relative to the i+1-th arm segment.

9. The method according to claim 1, characterized in that: The determining the working state of the robot arm based on the working parameter includes: Based on the working parameters, the weight of the object when the robot arm performs an object acquisition action is determined.

10. The method according to claim 5, characterized in that The determining the working state of the robot arm based on the working parameter includes: Based on the working parameters, determining the object acquisition weight of the at least one joint motor; Based on the object acquired weight of the at least one joint motor, the working state of the at least one joint motor of the robot arm is determined.

11. The method according to claim 10, characterized in that The step of determining the object acquisition weight of the at least one joint motor based on the working parameters comprises: For each joint motor of the at least one joint motor, a ratio of a product of the quadrature-axis current of the joint motor and the preset calibration coefficient to the lever arm length is determined as an object weight of the joint motor.

12. The method according to claim 10, characterized in that The step of determining the object acquisition weight of the at least one joint motor based on the working parameters comprises: Based on the quadrature axis current, arm length, preset calibration coefficient, moment of inertia, angular acceleration and friction torque of at least one joint motor of the robot arm, the object acquisition weight of the at least one joint motor is determined, wherein: W represents the weight of the object obtained by a single joint motor, I q is the quadrature axis current of a single joint motor, r is the arm length of the arm segment directly driven by the single joint motor, k is the preset calibration coefficient of the single joint motor, α is the angular acceleration of the arm segment directly driven by the single joint motor in motion, j is the moment of inertia of the joint where the single joint motor is located, F f It is the friction torque in the movement of the arm section directly driven by a single joint motor.

13. The method according to any one of claims 10 to 12, characterized in that The obtaining weight of the object based on the at least one joint motor and determining the working state of the at least one joint motor of the robotic arm comprises: If the object acquired weight of any joint motor of the at least one joint motor is greater than the corresponding safety weight threshold, it is determined that the robot arm is in an abnormal working state; otherwise, it is determined that the robot arm is in a normal working state; or If the object weight acquired by any joint motor of the at least one joint motor in the object weight acquisition detection for a specified number of consecutive times is greater than the corresponding safety weight threshold, it is determined that the robotic arm is in an abnormal working state; otherwise, it is determined that the robotic arm is in a normal working state.

14. The method according to claim 13, characterized in that If it is determined that the robotic arm is in an abnormal working state, the method further includes: generating a stop object acquisition instruction, and based on the stop object acquisition instruction, controlling the robot arm to cancel the object acquisition action; and Generate overweight alarm information.

15. The method according to claim 2, characterized in that Before obtaining the working parameters of the mechanical arm of the self-mobile cleaning device, the method further includes: Determine the target position of the object to be acquired required by the object acquisition action; The current posture of the robot arm is set as the grasping posture for the target position.

16. The method according to claim 15, characterized in that Before determining the target position of the object to be acquired required for the object acquisition action, the method further includes: The object to be acquired is identified by an object identification device, wherein the object identification device includes at least one of a visual sensor, a laser sensor, an ultrasonic sensor, and an infrared sensor.

17. The method according to claim 15, characterized in that The step of setting the current posture of the robot arm as a grasping posture for the target position comprises: Based on the target position, the posture configuration information of the robot arm when it is in the grasping posture is determined, wherein: The posture configuration information includes: The angle between the first arm segment of the mechanical arm closest to the self-moving cleaning device and the plane where the self-moving cleaning device is located; An offset angle of each arm segment other than the first arm segment in the robotic arm relative to the preceding arm segment in the direction adjacent to the first arm segment; and The arm length of each arm section in the robotic arm.

18. The method according to claim 1, characterized in that Before obtaining the working parameters of the mechanical arm of the self-mobile cleaning device, the method further includes: In response to a start-up instruction for the robotic arm, it is detected whether each joint motor of the robotic arm is in an effective working state, wherein if each joint motor of the robotic arm is in an effective working state, it is allowed to enter the step of obtaining the working parameters of the robotic arm from the mobile cleaning device.

19. The method according to claim 15, characterized in that After setting the current posture of the robot arm as the grasping posture for the target position, the method further includes: The robotic arm is adjusted from the grasping posture to the weighing posture.

20. The method according to claim 19, characterized in that The working parameters of the robot arm obtained from the mobile cleaning device include: During the adjustment process of adjusting the mechanical arm from the grasping posture to the weighing posture, monitoring the working parameters of the mechanical arm in real time to determine the working state of the mechanical arm based on the working parameters; as well as If the working state of the robot arm is an abnormal working state, the adjustment process is interrupted and an overweight protection strategy is executed; If the working state of the robot arm is a normal working state, continue the adjustment process.

21. The method according to claim 20, characterized in that The determining the working state of the robotic arm based on the working parameters further includes: If the object acquired weight of any joint motor of the at least one joint motor is greater than the corresponding safety weight threshold, it is determined that the robotic arm is in the abnormal working state; otherwise, it is determined that the robotic arm is in a normal working state; or If the object acquisition weight of any joint motor among the at least one joint motor in the object acquisition weight detection for a specified number of consecutive times is greater than the corresponding safety weight threshold, it is determined that the robotic arm is in the abnormal working state; otherwise, it is determined that the robotic arm is in a normal working state.

22. A robot arm control device, characterized in that: include: A robot arm working parameter acquisition unit, used to acquire working parameters of the robot arm of the self-moving cleaning device; The robot arm working state determining unit is used to determine the working state of the robot arm based on the working parameters.

23. The device according to claim 22, characterized in that The robot arm working parameter acquisition unit comprises: The first execution unit is used to obtain working parameters of the mechanical arm of the self-moving cleaning device when performing an object acquisition action, wherein the object acquisition action includes at least one of clamping, grabbing, and lifting.

24. The device according to claim 22, characterized in that The robot arm working parameter acquisition unit comprises: The second execution unit is used to obtain the working parameters of the robot arm of the self-moving cleaning device when the robot arm does not perform the object acquisition action.

25. The device according to claim 23 or 24, characterized in that The working parameters are obtained in real time.

26. The device according to claim 22, characterized in that The robot arm working parameter acquisition unit comprises: The fourth execution unit is used to obtain at least one of the quadrature-axis current, arm length, preset calibration coefficient, moment of inertia, angular acceleration and friction torque of at least one joint motor of the robotic arm, wherein the preset calibration coefficient is used to reflect the proportional relationship between the quadrature-axis current and the output torque in the at least one joint motor.

27. The device according to claim 26, characterized in that The method in which the robot arm working parameter acquisition unit acquires the quadrature axis current of at least one joint motor of the robot arm includes: The three-phase current of the at least one joint motor is collected, and the three-phase current is subjected to a Clark transformation to obtain the quadrature-axis current corresponding to the at least one joint motor.

28. The device according to claim 26, characterized in that The method in which the mechanical arm working parameter acquisition unit acquires the force arm length of at least one joint motor of the mechanical arm includes: For each joint motor of at least one joint motor of the robotic arm, the force arm length of the joint motor is determined as: Wherein, r represents the current arm length of the joint motor, n is the number of arm segments from the last arm segment of the robot arm to the current arm segment corresponding to the current joint motor, i represents the arm segment number, i∈[1,n], wherein the arm segment number of the last arm segment is 1, the arm segment number of the current arm segment is n, l i represents the arm length from the last arm section to the i-th arm section in the current arm section, θ i represents the angle between the i-th arm segment and the plane where the self-moving cleaning device is located.

29. The device according to claim 28, characterized in that Also includes: An angle determination unit, configured to determine θ if the current arm segment is the first arm segment of the robot arm closest to the self-moving cleaning device. i is the angle between the first arm section and the plane where the self-moving cleaning device is located; if the current arm section is not the first arm section, θ i =θ i+1 -μ i , where μ i represents the offset angle of the i-th arm segment relative to the i+1-th arm segment.

30. The device according to claim 22, characterized in that The robot arm working state determination unit is used to determine the weight of the object when the robot arm performs an object acquisition action based on the working parameters.

31. The device according to claim 26, characterized in that The robot arm working state determination unit comprises: an object acquisition weight determination unit, which determines the object acquisition weight of the at least one joint motor based on the working parameters; The working state determination unit is used to determine the working state of the at least one joint motor of the robotic arm based on the object acquired weight of the at least one joint motor.

32. The device according to claim 31, characterized in that The object weight determination unit comprises: The fifth execution unit is used to determine, for each joint motor of the at least one joint motor, a ratio of the product of the quadrature-axis current of the joint motor and the preset calibration coefficient to the lever arm length, as the object weight of the joint motor.

33. The device according to claim 31, characterized in that The object weight determination unit comprises: The sixth execution unit is used to determine the object acquisition weight of at least one joint motor of the robot arm based on the quadrature axis current, the arm length, the preset calibration coefficient, the moment of inertia, the angular acceleration and the friction torque of at least one joint motor of the robot arm, wherein: W represents the weight of the object obtained by a single joint motor, I q is the quadrature axis current of a single joint motor, r is the arm length of the arm segment directly driven by the single joint motor, K is the preset calibration coefficient of the single joint motor, α is the angular acceleration of the arm segment directly driven by the single joint motor, j is the moment of inertia of the joint where the single joint motor is located, F f It is the friction torque in the movement of the arm section directly driven by a single joint motor.

34. The device according to any one of claims 31 to 33, characterized in that The working state determination unit is used for: If the object acquisition weight of any one of the at least one joint motors is greater than the safety weight threshold, it is determined that the robotic arm is in an abnormal working state, otherwise, it is determined that the robotic arm is in a normal working state; or if the object acquisition weight of any one of the at least one joint motors in the object acquisition weight detection for a consecutive specified number of times is greater than the safety weight threshold, it is determined that the robotic arm is in an abnormal working state, otherwise, it is determined that the robotic arm is in a normal working state.

35. The device according to claim 34, characterized in that Also includes: a sixth execution unit, configured to generate a stop object acquisition instruction if it is determined that the robot arm is in an abnormal working state, and control the robot arm to cancel the object acquisition action based on the stop object acquisition instruction; The overweight alarm unit is used to generate overweight alarm information.

36. The device according to claim 35, characterized in that Also includes: A target position determination unit, used to determine a target position of an object to be acquired required for the object acquisition action before the robot arm working parameter acquisition unit acquires the working parameters; The grasping posture setting unit is used to set the current posture of the robot arm as the grasping posture for the target position.

37. The device according to claim 36, characterized in that Also includes: The object identification unit to be acquired is used to identify the object to be acquired through an object identification device before the target position determination unit determines the target position, wherein the object identification device includes at least one of a visual sensor, a laser sensor, an ultrasonic sensor, and an infrared sensor.

38. The device according to claim 36, characterized in that The grasping posture setting unit is used for: Based on the target position, determine the posture configuration information of the robot arm when it is in the grasping posture, wherein the posture configuration information includes: The angle between the first arm segment of the mechanical arm closest to the self-moving cleaning device and the plane where the self-moving cleaning device is located; An offset angle of each arm segment other than the first arm segment in the robotic arm relative to the preceding arm segment in the direction adjacent to the first arm segment; and The arm length of each arm section in the robotic arm.

39. The device according to claim 22, characterized in that Also includes: A robot arm initial detection unit is used to detect whether each joint motor of the robot arm is in a valid working state in response to a startup instruction for the robot arm before the robot arm working parameter acquisition unit acquires the working parameters, wherein if each joint motor of the robot arm is in a valid working state, the robot arm working parameter acquisition unit is allowed to acquire the working parameters.

40. The device according to claim 36, characterized in that Also includes: The weighing posture adjustment unit is used to adjust the mechanical arm from the grasping posture to the weighing posture after the grasping posture setting unit sets the current posture of the mechanical arm to the grasping posture for the target position.

41. The device according to claim 40, characterized in that The robot arm working parameter acquisition unit comprises: an adjustment process monitoring unit, configured to monitor the working parameters of the robotic arm in real time during the adjustment process of adjusting the robotic arm from the grasping posture to the weighing posture, so as to determine the working state of the robotic arm based on the working parameters; a sixth execution unit, configured to interrupt the adjustment process and execute an overweight protection strategy if the working state of the robot arm is an abnormal working state; The seventh execution unit is used to continue the adjustment process if the working state of the robot arm is a normal working state.

42. The device according to claim 41, characterized in that The mechanical arm working state determination unit is used for: If the object acquisition weight of any one of the at least one joint motors is greater than the corresponding safety weight threshold, it is determined that the robotic arm is in the abnormal working state; otherwise, it is determined that the robotic arm is in the normal working state; or if the object acquisition weight of any one of the at least one joint motors in the object acquisition weight detection is greater than the corresponding safety weight threshold, it is determined that the robotic arm is in the abnormal working state; otherwise, it is determined that the robotic arm is in the normal working state.

43. A self-propelled cleaning device, characterized in that: include: at least one processor; and, a memory communicatively coupled to the at least one processor; The memory stores instructions executable by the at least one processor, wherein the instructions are configured to enable the processor to execute the method described in any one of claims 1 to 21.

44. A computer-readable storage medium, characterized in that Computer executable instructions are stored, and the computer executable instructions are configured to perform the method according to any one of claims 1 to 21.

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